Choose from a curated set of bioinformatics and computational biology programs. Build real skills, work on meaningful projects, and earn a verified certificate.
Learn how machine learning and deep learning models are applied to biological data from protein folding to drug discovery.
8 Weeks
Online
Understand Genome-Wide Association Studies from study design to interpretation — including statistical models and population genetics.
8 Weeks
Online
Apply computational tools to predict antigens, model immune responses, and design multi-epitope vaccines in silico.
8 Weeks
Online
Explore beyond reference genomes — learn to construct, annotate, and analyze pangenomes for population-level genomic studies.
8 Weeks
Online
Analyze microbial communities from environmental and clinical samples using next-gen sequencing and bioinformatics pipelines.
8 Weeks
Online
MgBio has helped learners build skills, complete real research projects, and grow their careers across 50+ universities and industries.
"Over two months, I explored the intersection of AI, ML, and biosciences, diving deep into Python-based model building, preprocessing, clustering, supervised & unsupervised learning. This journey sharpened my technical skills and analytical thinking."
"I learned how AI & Machine Learning can be applied in biosciences from Python programming and supervised/unsupervised learning to handling biological datasets for real-world applications. This milestone has strengthened my passion for combining Biotechnology with AI."
"This experience was more than just a training, it was a journey of growth. From learning the foundations of AI and ML to applying them in biosciences and real-world biological projects, I've gained both theoretical knowledge and practical skills."
"This experience gave me valuable learning opportunities in applying AI to biological research. I gained hands-on skills at the intersection of AI and biology that will greatly support my future research career."
"Recognized as 1st Achiever for individual performance and 3rd position in Top Performing Group out of 23 groups. The most valuable takeaway was developing expertise in applying machine learning using Python to complex biological datasets."
"I gained hands-on experience at the intersection of AI and biology, enhancing my understanding of how computational tools can be applied to solve complex biological problems. I look forward to applying these skills in future research."
"This internship bridged the gap between biosciences and modern computational approaches. The program covered Foundations of AI & ML and Applied ML in Biosciences — truly inspiring me to explore bioinformatics and data-driven biology."
"During my metagenomics internship, I worked on implementing DBSCAN clustering for microbial data, applying UMAP for dimensionality reduction, and exploring BioLLM models for sequence embeddings — a truly enriching research experience."
